Ying Liu

Cell-Based Network Optimization Model for Staged Evacuation Planning Under Emergencies

Staged evacuation is widely used in emergency situations in which different parts of the target network may suffer different levels of severity over different time windows. By evacuating those populations in the network via an optimized sequence, the staged evacuation strategy can best use available roadway capacity, optimally distribute the total demand over the evacuation time horizon, and thus minimize the network congestion level. This study proposes a cell-based network model to capture critical characteristics associated with staged evacuation operations. The proposed model shows the ability to reflect incident impacts and arrival patterns of evacuees in computing the optimal starting time and routes for each evacuation zone. Preliminary numerical results have demonstrated the potential for applying the proposed staged evacuation model in real-world emergency management and planning.

Corridor-Based Emergency Evacuation System for Washington, D.C.: System Development and Case Study

The evacuation of large municipal areas in an efficient manner during emergencies and disasters is one of the critical tasks of emergency management agencies. This paper presents a corridor-based emergency evacuation system and an example application of the system for the Washington, D.C., metropolitan area. The proposed system features flexibility by accounting for various critical issues associated with both planning and real-time operations, including the integration of data from multiple sources, network decomposition, network-level traffic routing, contraflow design, staged evacuation, optimal signal timing, and the incorporation of pedestrian and bus operations. Under a hypothetical emergency scenario for Union Station in Washington, D.C., the proposed system demonstrated its effectiveness at producing evacuation routing strategies, identifying potential bottlenecks, and evaluating the performance of evacuation operations.

Developments and Applications of Simulation-Based Online Travel Time Prediction System: Traveling to Ocean City, Maryland

The framework and field application of a simulation-based online system for travel time prediction are presented. The proposed system is designed to contend with most critical issues associated with real-time operations, which include estimation of missing volumes, detection of incidents, data filtering, and computation of traffic volumes for projected time intervals so as to activate the simulation function. The proposed system was deployed on two routes of 30 mi between Salisbury and Ocean City, Maryland, with a total of 10 detectors. The preliminary application results clearly indicate that with proper integration the proposed system offers a cost-effective tool for real-time travel time prediction.

Detector Placement Strategies for Freeway Travel Time Estimation

One popular class of approaches to estimate freeway corridor travel time is based on measured or estimated speed data from roadside detectors. In most estimation practices, using either simulated or actual data, detectors are assumed to evenly distribute with a close spacing of around half mile. Unfortunately, this detector location scheme will be too costly for most freeway corridors under limited budget. To contend with this issue, this paper examines some widely used estimation algorithms under various traffic conditions with different detector spacing, and then proposes a set of strategies for locating detectors. Numerical results, based on traffic conditions on 1-70 corridor of Maryland, have demonstrated the promising properties of our proposed strategies under recurrent congestion pattern

An integrated emergency evacuation system for real-time operations - a case study of Ocean City, Maryland under hurricane attacks

The consecutive hurricane attacks to US coastline have drawn significant attentions to evacuation operations related issues. To better prepare the state of Maryland for potential hurricanes, this study presents an emergency evacuation system that integrates both optimization and microscopic simulation methods. The optimization module applies a two-level process to generate the preliminary optimal control plans, which is based on a revised cell transmission formulation for large-scale network applications. Using the optimized results as the initial input, the simulation module takes into account various operational constraints and driver responses that are difficult to be captured realistically with mathematical formulations. The proposed system also features its flexibility for potential users to adjust the optimized plans in both the planning phase and real-time operations based on the results of simulation evaluation. The case study with the data from Ocean City, Maryland during hurricane attacks has demonstrated the potential of the proposed system for evacuation of traffic flows in large-scale networks within a given time window.

Estimation of Freeway Travel Time Based on Sparsely Distributed Detectors

This study presents a new approach for estimating travel time information along freeway corridors, which experience recurrent congestions but have only a limited number of available detectors due to budget constraints. The proposed iterative estimation procedure, based on a set of empirically calibrated regression models, intends to rebuild the relations between travel times and accumulated flows within each segment of the target freeway corridor. To evaluate the effectiveness of the proposed methodology, this study has conducted extensive numerical experiments with simulated data from a CORSIM simulator. Experimental results under various traffic volume levels have revealed that the proposed method offers a promising property for use in travel time estimation based on sparsely distributed sensors.

OPTIMAL DETECTOR LOCATIONS FOR OD MATRIX ESTIMATION

This paper has investigated critical issues associated with Optimal Detector Locations for OD matrix estimation, including a discussion of limitations embedded in existing models and algorithms. A heuristic algorithm has been proposed for identifying the optimal set of detector locations under a given budget constraint for effective OD matrix estimation. The numerical experiment results have indicated that the proposed algorithm is quite promising for potential applications.

Emergency incident management, benefits and operational issues performance and benefits evaluation of CHART

The need to implement an effective incident management systems (IMS) has received increasing attention by general public, media and policy makers, that in turn has required transportation agencies to perform a rigorous evaluation over any implemented plan. Since 1996, the Maryland State Highway Administration (MSHA) has conducted a comprehensive evaluation of its incident response and management program, named CHART. The evaluation study consisted of two phases. Whereas the focus of Phase 1 was on the reliable assess of system performance including incident detection, response, clearance and duration, the core of Phase 2 was to develop the methodology and to estimate resulting system benefits from data available in the CHART incident operations record.

Arterial signal optimization for emergency evacuation

Abstract This paper presents a mixed-integer model for design of arterial signal control strategies during emergency evacuation. The proposed model can effectively take into account various complex operational issues such as critical intersection selection, demand rerouting, and signal timing. The control objective is to maximize the efficiency of the primary evacuation arterial, but not incur excessive waiting time and queues on its side streets. To evaluate the effectiveness of the proposed model under various demand levels and control objectives, this study has employed one major evacuation corridor in Washington D.C. as the target route for numerical experiments. The results of extensive simulation experiments reveal that the proposed method for signal optimization offers the potential for real-world applications.